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20232026
most citedUnified Medical Image Segmentation with State Space Modeling Snake

1 citations · 2 across the 17 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

TEAMS: Text-prompted spatiotEmporal dual-heAd Mamba Snake

Ruicheng Zhang, Jianhui Lei, Kaiwen Shen +6

Deep snake is a promising family of instance segmentation methods that accurately predicts object-level contours, thereby overcoming common pixel-level misclassification issues suc…

cs.CV2026

SC-Diff: Semantically Calibrated Diffusion for Visible-to-Infrared Image Translation

Junyin Zhang, Siyu Huang, Jianxiong Ye +4

Visible-to-infrared image translation provides a practical way to expand infrared training data using abundant visible images. Diffusion models are promising for this task because…

cs.CV2026

PhysEditWorld: A Large-Scale Dataset Toward Physics-Editable World Models

Bin Hu, Yanwen Ma, Jiehui Huang +14

Recent game world models can synthesize visually plausible, action-conditioned rollouts. However, their interaction behaviors often remain limited to exploratory or wandering traje…

cs.AI2026

Learning Visual Spatial Planning from Symbolic State via Modality-Gap-Aware Self-Distillation

Haocheng Luo, Jiahui Liu, Ruicheng Zhang +8

While Vision-Language Models excel at general multimodal understanding, they still struggle with visual spatial planning. We attribute this limitation to a perception--reasoning mo…

cs.CV2026

RoboStereo: Dual-Tower 4D Embodied World Models for Unified Policy Optimization

Ruicheng Zhang, Guangyu Chen, Zunnan Xu +5

Scalable Embodied AI faces fundamental constraints due to prohibitive costs and safety risks of real-world interaction. While Embodied World Models (EWMs) offer promise through ima…

cs.CV2026

Identity-Consistent Video Generation under Large Facial-Angle Variations

Bin Hu, Zipeng Qi, Guoxi Huang +6

Single-view reference-to-video methods often struggle to preserve identity consistency under large facial-angle variations. This limitation naturally motivates the incorporation of…